15 citations · 31 across the 15 of their papers we have counts for
7 papers · 1 filter
Gaming the Answer Matcher: Examining the Impact of Text Manipulation on Automated Judgment
Manas Khatore, Sumana Sridharan, Kevork Sulahian +2
Automated answer matching, which leverages LLMs to evaluate free-text responses by comparing them to a reference answer, shows substantial promise as a scalable and aligned alterna…
Emergent Persuasion: Will LLMs Persuade Without Being Prompted?
Vincent Chang, Thee Ho, Sunishchal Dev +4
With the wide-scale adoption of conversational AI systems, AI are now able to exert unprecedented influence on human opinion and beliefs. Recent work has shown that many Large Lang…
Mitigating Self-Preference by Authorship Obfuscation
Taslim Mahbub, Shi Feng
Language models (LMs) judges are widely used to evaluate the quality of LM outputs. Despite many advantages, LM judges display concerning biases that can impair their integrity in…
Parameter-Efficient Construction of the Rashomon Slice for Concept Bottleneck Models
Shihan Feng, Cheng Zhang, Michael Xi +3
In many machine learning problems, there may exist multiple models that achieve nearly identical predictive performance while relying on fundamentally different internal logic. How…
DeepDive: Advancing Deep Search Agents with Knowledge Graphs and Multi-Turn RL
Rui Lu, Zhenyu Hou, Zihan Wang +6
Augmenting large language models (LLMs) with browsing tools substantially improves their potential as deep search agents to solve complex, real-world tasks. Yet, open LLMs still pe…
AI Debate Aids Assessment of Controversial Claims
Salman Rahman, Sheriff Issaka, Ashima Suvarna +11
As AI grows more powerful, it will increasingly shape how we understand the world. But with this influence comes the risk of amplifying misinformation and deepening social divides-…
Do LLM Evaluators Prefer Themselves for a Reason?
Wei-Lin Chen, Zhepei Wei, Xinyu Zhu +2
Large language models (LLMs) are increasingly used as automatic evaluators in applications such as benchmarking, reward modeling, and self-refinement. Prior work highlights a poten…